Participatory Learning in Linked Open Data

摘要

The introduction of Resource Description Framework (RDF) as a fundamental data representation format of Semantic Web is changing a way how data is stored on the Internet. The intrinsic features of RDF data, i.e., its interconnections and simplicity of expressing information as triples: two entities connected by a property, provide new possibilities of analyzing and absorbing information. The extended format of participatory learning methodology based on propositions is an attractive way of integrating new knowledge. It mimics a human-like way of accepting new facts, expressed as propositions, that could be in contradiction with already known facts. This paper proposes a method of application of participatory learning to integrate RDF triples collected on the web. The approach presented here includes the concept of conjunctive and disjunctive variables. The learning process is presented, and a simple case study is provided.